assignment4

10.5.1

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## ✔ readr   1.1.1     ✔ forcats 0.2.0

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is.tibble(mtcars)

## [1] FALSE

So, if we can open the data.frame with tibble, then it’s a tibble data.frame. If we have to open it with as_tibble(), then it is a regular data.frame. And also, we can use is.tibble() to find out if it is a tibble or just a normal data.frame.

10.5.2

## [1] a
## Levels: a

## [1] a
## Levels: a

if we want to subset some data from regular data.frame, we have to consider about the rows and columns. However, if we use tibble, we could just consider the columns. ##10.5.3

var <- “mpg” var[[“mpg”]] var %>% .$mpg var %>% .[[“mpg”]]

10.5.4

10.5.4.1

##  [1]  1  2  3  4  5  6  7  8  9 10

10.5.4.2

10.5.4.3

10.5.4.4

10.5.5

enframe() converts named atomic vectors or lists to two-column data frames. For unnamed vectors, the natural sequence is used as name column.

10.5.6

print.tbl_df

12.6.1

we use na.rm = T in this case is reasonable, because there are lots of NA values in the data which is useless. we can use count(cases=NA) find out the all these missing values.

count(who,cases = NA)

12.6.2

The code will not be separated properly into the three columns new, var, and sexage.

12.6.3

12.6.4